Preparation and characterization of gelatin from collagen biomass obtained through a pH-shifting process of mechanically separated turkey meat
Bibliographic record
Abstract
Gelatins were extracted from mechanically separated turkey meat following 2 different approaches. The first method was based on a 2-stage batch extraction at 50 and 60°C, respectively, whereas the second method consisted of recovering gelatin from a collagen biomass obtained during a pH-shifting process. The yield of gelatin produced by the latter method was twice that obtained by the former method (13.51 and 6.36%, respectively). The chemical composition, as well as the rheological and the functional properties, of all extracted gelatins were evaluated. Gelatin recovered from the collagen biomass had higher molecular weight components and significantly greater (P < 0.05) bloom value (353.2 g) compared with thermally extracted gelatins. However, gelatin extracted at 60°C possessed higher (P < 0.05) foaming properties, as well as better emulsifying activity, than gelatin extracted from the 50°C treatment and the collagen biomass. The present study revealed that high-quality gelatins can be prepared from mechanically separated turkey meat through precipitation and thermal solubilization of collagen biomass obtained during a pH-shifting process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".